The Prediction & Behavior ML team is responsible for developing machine-learned models that understand the full scene around our vehicle and forecast the behavior for other agents, our own vehicle’s actions, and for offline applications. To solve these problems we develop deep learning algorithms that can learn behaviors from data and apply them on-vehicle to influence our vehicle’s driving behavior and offline to provide learned models to autonomy simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team necessarily works very closely with the Planner team in the advancement of our overall vehicle behavior. The Prediction & Behavior ML team also works closely with our Perception, Simulation, and Systems Engineering teams on many cross-team initiatives.

You will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work with different research teams and squads across multiple areas led by our Director of Science, Prof. Vittorio Ferrari, and directly impact our solutions that are used worldwide by over 55,000 businesses.

If you have seen the full ML lifecycle from ideation through implementation, testing and release, and you have a passion for large data, large model training and building solutions with clean code, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.

Location Madrid, ESP

Description Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site.

The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content?

We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables.

Location Palo Alto, CA

Description Amazon is looking for talented Postdoctoral Scientists to join our Stores Foundational AI team for a one-year, full-time research position.

The Stores Foundational AI team builds foundation models for multiple Amazon entities, such as ASIN, customer, seller and brand. These foundation models are used in downstream applications by various partner teams in Stores. Our team also invest in building foundation model for image generation, optimized for product image generation. We leverage the latest development to create our solutions and innovate to push state of the art.

The Postdoc is expected to conduct research and build state-of-the-art algorithms in video understanding and representation learning in the era of LLMs. Specifically, Designing efficient algorithms to learn accurate representations for videos. Building extensive video understanding capabilities including various content classification tasks. Designing algorithms that can generate high-quality videos from set of product images. Improve the quality of our foundation models along the following dimensions: robustness, interpretability, fairness, sustainability, and privacy.

Excited to see you at CVPR! We’ll be at booth 1404. Come see us to talk more about roles.

Our team consists of people with diverse software and academic experiences. We work together towards one common goal: integrating the software, you'll help us build into hundreds of millions of vehicles.

As a Research Engineer, you will work collaboratively to improve our models and iterate on novel research directions, sometimes in just days. We're looking for talented engineers who would enjoy applying their skills to deeply complex and novel AI problems. Specifically, you will:

• Apply and extend the Helm proprietary algorithmic toolkit for unsupervised learning and perception problems at scale
• Carefully execute the development and maintenance of tools used for deep learning experiments designed to provide new functionality for customers or address relevant corner cases in the system as a whole
• Work closely with software and autonomous vehicle engineers to deploy algorithms on internal and customer vehicle platforms

Location Sunnyvale, CA Bellevue, WA

Description Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique possibility to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. You will be part of a team committed to pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work on scale. This position requires experience with developing Multi-modal LLMs and Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.

Location San Francisco, CA

Description Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.

You will be managing a team within the Music Machine Learning and Personalization organization that is responsible for developing, training, serving and iterating on models used for personalized candidate generation for both Music and Podcasts.

About the role As a detail-oriented and experienced Data Annotation QA Coordinator you will be responsible for both annotating in-house data-sets and ensuring the quality assurance of our outsourced data annotation deliveries.Your key responsibilities will include text, audio, image, and video annotation tasks, following detailed guidelines. To be successful in the team you will have to be comfortable working with standard tools and workflows for data annotation and possess the ability to manage projects and requirements effectively.

You will join a group of more than 40 Researchers and Engineers in the R&D department. This is an open, collaborative and highly supportive environment. We are all working together to build something big - the future of synthetic media and programmable video through Generative AI. You will be a central part of a dynamic and vibrant team and culture.

Please, note, this role is office-based. You will be working at our modern friendly office at the very heart of London.

Redmond, Washington, United States

Overview We are seeking a highly skilled and passionate Research Scientist to join our Responsible & OpenAI Research (ROAR) team in Azure Cognitive Services.

As a Research Scientist, you will play a key role in advancing the field of Responsible Artificial Intelligence (AI) to ensure safe releases of the rapidly advancing AI technologies, such as GPT-4, GPT-4V, DALL-E 3 and beyond, as well as to expand and enhance our standalone Azure AI Content Safety Service.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities Conduct cutting-edge research to develop Responsible AI definitions, methodologies, algorithms, and models for both measurement and mitigation of AI risks. Stay abreast of the latest advancements in the field and contribute to the scientific community through publications at top venues. Contribute to the development of Responsible AI policies, guidelines, and best practices and ensure the practical implementation of these guidelines within various AI technology stacks across Microsoft, promoting a consistent approach to Responsible AI. Enable the safe release of new Azure OpenAI Service features, expand and enhance the Azure AI Content Safety Service with new detection technologies. Develop innovative approaches to address AI safety challenges for diverse customer scenarios. Other: Embody our Culture and Values

ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

ASML’s Optical Sensing (Wafer Alignment Sensor and YieldStar) department in Wilton, Connecticut is seeking a Design Engineer to support and develop complex optical/photonic sensor systems used within ASML’s photolithography tools. These systems typically include light sources, detectors, optical/electro-optical components, fiber optics, electronics and signal processing software functioning in close collaboration with the rest of the lithography system. As a design engineer, you will design, develop, build and integrate optical sensor systems.

Role and Responsibilities Use general Physics, Optics, Software knowledge and an understanding of the sensor systems and tools to develop optical alignment sensors in lithography machines Have hands-on sills of building optical systems (e.g. imaging, testing, alignment, detector system, etc.) Have strong data analysis sills to evaluate sensor performance and troubleshooting Leadership:

Lead executing activities for determining problem root cause, execute complex tests, gather data and effectively communicate results on different levels of abstraction (from technical colleagues to high level managers) Lead engineers in various competencies (e.g. software, electronics, equipment engineering, manufacturing engineering, etc.) in support of feature delivery for alignment sensors Problem Solving: Troubleshooting complex technical problems Develop/debug data signal processing algorithms Develop and execute test plans in order to determine problem root cause Communications/Teamwork: Draw conclusions based on the input from different stakeholders Capability to clearly communicate the information on different level of abstraction Programming: Implement data analysis techniques into functioning MATLAB codes Optimization skills GUI building experience Familiarly with LabView and Python Some travel (up to 10%) to Europe, Asia and within the US can be expected

Location Mountain View, CA

Description Gatik is thrilled to be at CVPR! Come meet our team at booth 1831 to talk about how you could make an impact at the autonomous middle mile logistics company redefining the transportation landscape.

Who we are: Gatik, the leader in autonomous middle mile logistics, delivers goods safely and efficiently using its fleet of light & medium-duty trucks. The company focuses on short-haul, B2B logistics for Fortune 500 customers including Kroger, Walmart, Tyson Foods, Loblaw, Pitney Bowes, Georgia-Pacific, and KBX; enabling them to optimize their hub-and-spoke supply chain operations, enhance service levels and product flow across multiple locations while reducing labor costs and meeting an unprecedented expectation for faster deliveries. Gatik’s Class 3-7 autonomous box trucks are commercially deployed in multiple markets including Texas, Arkansas, and Ontario, Canada.

About the role: We are seeking passionate Senior/Staff Software Engineers, who have strong fundamentals in software development practices and are experts in C++ language in production-oriented environment. The ideal candidate is a highly experienced C++ developer with a passion for enabling the world's first safe, reliable & efficient network of autonomous vehicles. You will partner with the research and software engineers to design, develop, test and validate AV features for our autonomous fleet.

This role will be onsite at our Mountain View office.

What you'll do: +Design, implement, integrate, and support real-time mission-critical software for the Gatik’s autonomy stack +Work with the research engineers to develop maintainable, testable and robust software designs +Architect and implement solutions to complex issues between components partitioned across the large software stack +Be at the forefront of guiding & ensuring best SDLC practices while contributing to improving the safety in the core autonomy stack +Collaborate with the Infrastructure and DevOps teams for efficient, secure and scalable software delivery to a network of Gatik’s autonomous fleet
+Guide and mentor autonomy researchers and algorithm developers to make sure their components are running efficiently and with optimal compute and memory usage +Review and refine technical requirements and translate them into high-level design & plans to support the development of safe AV technology +Conduct code and design reviews and advise on technical matters

Click the apply button below to see the full job description and apply

Overview We are seeking an exceptionally talented Postdoctoral Research Fellow to join our interdisciplinary team at the forefront of machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. This position is hosted by the Stanford Translational AI (STAI) in Medicine and Mental Health Lab (PI: Dr. Ehsan Adeli, https://stanford.edu/~eadeli), as part of the Department of Psychiatry and Behavioral Sciences at Stanford University. The postdoc will have the opportunity to directly collaborate with researchers and PIs within the Computational Neuroscience Lab (CNS Lab) in the School of Medicine and the Stanford Vision and Learning (SVL) lab in the Computer Science Department. These dynamic research groups are renowned for groundbreaking contributions to artificial intelligence and medical sciences.

Project Description The successful candidate will have the opportunity to work on cutting-edge projects aimed at building large-scale models for neuroimaging and neuroscience through innovative AI technologies and self-supervised learning methods. The postdoc will contribute to building a large-scale foundation model from brain MRIs and other modalities of data (e.g., genetics, videos, text). The intended downstream applications include understanding the brain development process during the early ages of life, decoding brain aging mechanisms, and identifying the pathology of different neurodegenerative or neuropsychiatric disorders. We use several public and private datasets including but not limited to the Human Connectome Project, UK Biobank, Alzheimer's Disease Neuroimaging Initiative (ADNI), Parkinson’s Progression Marker Initiative (PPMI), Open Access Series of Imaging Studies (OASIS), Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA), Adolescent Brain Cognitive Development (ABCD), and OpenNeuro.

Key Responsibilities Conduct research in machine learning, computer vision, and medical image analysis, with applications in neuroimaging and neuroscience. Develop and implement advanced algorithms for analyzing medical images and other modalities of medical data. Develop novel generative models. Develop large-scale foundation models. Collaborate with a team of researchers and clinicians to design and execute studies that advance our understanding of neurological disorders. Mentor graduate students (Ph.D. and MSc). Publish findings in top-tier journals and conferences. Contribute to grant writing and proposal development for securing research funding.

Qualifications PhD in Computer Science, Electrical Engineering, Neuroscience, or a related field. Proven track record of publications in high-impact journals and conferences including ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, MICCAI, Nature, and JAMA. Strong background in machine learning, computer vision, medical image analysis, neuroimaging, and neuroscience. Excellent programming skills in Python, C++, or similar languages and experience with ML frameworks such as TensorFlow or PyTorch. Ability to work independently and collaboratively in an interdisciplinary team. Excellent communication skills, both written and verbal.

Benefits Competitive salary and benefits package. Access to state-of-the-art facilities and computational resources. Opportunities for professional development and collaboration with leading experts in the field. Participation in international conferences and workshops. Working at Stanford University offers access to world-class research facilities and a vibrant intellectual community. The university provides numerous opportunities for interdisciplinary collaboration, professional development, and cutting-edge innovation. Additionally, being part of Stanford opens doors to a global network of leading experts and industry partners, enhancing both career growth and research impact.

Apply For full consideration, send a complete application via this form: https://forms.gle/KPQHPGGeXJcEsD6V6

San Jose, CA

The Media Analytics team at NEC Labs America is seeking outstanding researchers with backgrounds in computer vision or machine learning. Candidates must possess an exceptional track record of original research and passion to create high impact products. Our key research areas include autonomous driving, open vocabulary perception, prediction and planning, simulation, neural rendering, agentic LLMs and foundational vision-language models. We have a strong internship program and active collaborations with academia. The Media Analytics team publishes extensively at top-tier venues such as CVPR, ICCV or ECCV.

To check out our latest work, please visit: https://www.nec-labs.com/research/media-analytics/

Qualifications: 1. PhD in Computer Science (or equivalent) 2. Strong publication record at top-tier computer vision or machine learning venues 3. Motivation to conduct independent research from conception to implementation.

Canberra/Australia

We are looking for new outstanding PhD students for the upcoming scholarship round (application is due on 31st August 2024) at the Australian National University (ANU is ranked #30 in the QS Ranking 2025) or possibly at another Australian universities.

We are looking for new PhD students to work on new problems that may span over (but are not limited to) "clever" adapting of Foundation Models, LLMs, diffusion models (LORAs etc.,), NERF, or design of Graph Neural Networks, design of new (multi-modal) Self-supervised Learning and Contrastive Learning Models (masked models, images, videos, text, graphs, time series, sequences, etc. ) or adversarial and/or federated learning or other contemporary fundamental/applied problems (e.g., learning without backprop, adapting FMs to be less resource hungry, planning and reasoning, hyperbolic geometry, protein property prediction, structured output generative models, visual relation inference, incremental/learning to learn problems, low shot, etc.)

To succeed, you need an outstanding publication record, e.g., one or more first-author papers in venues such CVPR, ICCV, ECCV, AAAI, ICLR, NeurIPS, ICML, IJCAI, ACM KDD, ACCV, BMVC, ACM MM, IEEE. Trans. On Image Processing, CVIU, IEEE TPAMI, or similar (the list is non-exhaustive). Non-first author papers will also help if they are in the mix. Some patents and/or professional experience in Computer Vision, Machine Learning or AI are a bonus. You also need a good GPA to succeed.

We are open to discussing your interests and topics, if you reach out, we can discuss what is possible. Yes, we have GPUs.

If you are interested, reach out for an informal chat with Dr. Koniusz. I am at CVPR if you want to chat?): piotr.koniusz@data61.csiro.au (or piotr.koniusz@anu.edu.au, www.koniusz.com)

We are seeking a highly motivated candidate for a fully funded postdoctoral researcher position to work in 3D computer graphics and 3D computer vision.

The successful candidate will join the 3D Graphics and Vision research group led by Prof. Binh-Son Hua at the School of Computer Science and Statistics, Trinity College Dublin, Ireland to work on topics related to generative AI in the 3D domain. The School of Computer Science and Statistics at Trinity College Dublin is a collegiate, friendly, and research-intensive centre for academic study and research excellence. The School has been ranked #1 in Ireland, top 25 in Europe, and top 100 Worldwide (QS Subject Rankings 2018, 2019, 2020, 2021).

The postdoctoral researcher is expected to conduct fundamental research and publish in top-tier computer vision and computer graphics conferences (CVPR, ECCV, ICCV, SIGGRAPH) and journals (TPAMI, IJCV). Other responsibilities include supporting graduate or undergraduate students with technical guidance and engagement in other research activities such as paper reviews, reading group, workshop organization, etc.

The start date of the position is August 01, 2024. Contract duration is 1 year with the option of renewing for a second year. The successful candidate will require the following skills and knowledge: • PhD in Computer Science or related fields; • Strong tracked records in 3D computer graphics, 3D computer vision; • Hands-on experience in training deep models and generative models is required; • Hands-on experience and relevant skills in computer graphics and computer vision application development such as OpenGL, OpenCV, CUDA, Blender is desirable; • Strong programming skills in C++, Python. Capability in implementing systems from research papers and open-source software. • Additional background in math, statistics, or physics is an advantage.

Applicants should provide the following information: • A comprehensive CV including a full list of publications; • The name and contact details of two referees. One of the referees should be the applicant’s PhD supervisor; • Two representative papers by the applicant. Interested candidates should email their applications to Binh-Son Hua (https://sonhua.github.io) directly. Applications will be reviewed on a rolling basis until the position has been filled.